Search results for "Generative AI System Design"
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Writing AI Prompts For Dummies
Learn the art of writing effective AI prompts and break into an exciting new career field Writing AI Prompts For Dummies gets you started on the path toward becoming an “AI psychologist” capable of getting all types of output from AI systems. This book walks you through the process of mining great results from leading platforms, so you can save time, solve problems, explore creative ideas, conduct research, and beyond. Even if you’re brand new to using AI chatbots, you’ll be able to follow the jargon-free explanations and instructions inside to learn how to ask questions and make requests in terms any AI can understand. Then, you can convert your new skill into greater productivity in your life, or even into a new career. Prompt engineering is a fast-growing career opportunity with six-figure salaries attached. Who knows? This Dummies guide could be your launchpad to a future as an AI whisperer. Explore the top AI chatbots, creativity engines, and productivity tools Learn how to write basic text prompts that generate concise, effective outputCreate AI-generated photos and illustrations that match your visionSave time writing code, designing websites, or conducting research When asked “Who needs to learn prompt engineering?” ChatGPT clarifies: professionals, creatives, educators, scientists, and entrepreneurs in many fields can benefit an enhanced ability to use AI productively. And for anyone working in AI, natural language processing, or related areas, Writing AI Prompts For Dummies is simply a must.
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Artificial Intelligence Programming with Python
A hands-on roadmap to using Python for artificial intelligence programming In Practical Artificial Intelligence Programming with Python: From Zero to Hero, veteran educator and photophysicist Dr. Perry Xiao delivers a thorough introduction to one of the most exciting areas of computer science in modern history. The book demystifies artificial intelligence and teaches readers its fundamentals from scratch in simple and plain language and with illustrative code examples. Divided into three parts, the author explains artificial intelligence generally, machine learning, and deep learning. It tackles a wide variety of useful topics, from classification and regression in machine learning to generative adversarial networks. He also includes: Fulsome introductions to MATLAB, Python, AI, machine learning, and deep learningExpansive discussions on supervised and unsupervised machine learning, as well as semi-supervised learningPractical AI and Python “cheat sheet” quick referencesThis hands-on AI programming guide is perfect for anyone with a basic knowledge of programming—including familiarity with variables, arrays, loops, if-else statements, and file input and output—who seeks to understand foundational concepts in AI and AI development.
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Information and Knowledge System
The purpose of this book is to question the relationships involved in decision making and the systems designed to support it: decision support systems (DSS). The focus is on how these systems are engineered; to stop and think about the questions to be asked throughout the engineering process and, in particular, about the impact designers’ choices have on these systems. This therefore involves identifying the elements of the problem of decision support systems engineering: the main objects and dimensions to be considered and the relationships they involve, issues at the levels of the decision-maker, of the organization (and even of society), the general approach to which to subscribe and so on.
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Computing, Communication, And Sustainable Energy Technologies
This book brings together recent research and innovative ideas that integrate computing, intelligent communication, and energy-efficient electronic technologies to support sustainable development. The volume highlights advancements in sustainable electronic design, renewable energy integration, smart computing approaches, and intelligent communication frameworks. Emphasis is placed on low-power electronics, energy harvesting, IoT-based energy solutions, smart grids, and AI-driven energy management systems that enable environmentally responsible technologies. Key features of this book include:An overview of current research trends in sustainable electronics, emerging energy technologies, and intelligent computing and communication systems.Practical models, designs, and architectures showcasing real-world applications of energy-efficient and smart electronic systems.Discussions on applications in renewable energy systems, smart grids, IoT, electric vehicles, and power-aware intelligent devices.Insights into challenges, opportunities, and future research directions in sustainable and energy-aware technologies.This book is intended for research scholars, academicians, undergraduate and postgraduate students, Ph.D. candidates, industry professionals, engineers, technologists, and researchers who seek to advance their knowledge of sustainable electronics, emerging energy technologies, and intelligent systems for a greener and more energy-efficient future.
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Machine Translation and Transliteration involving Related, Low-resource Languages
Machine Translation and Transliteration involving Related, Low-resource Languages discusses an important aspect of natural language processing that has received lesser attention: translation and transliteration involving related languages in a low-resource setting. This is a very relevant real-world scenario for people living in neighbouring states/provinces/countries who speak similar languages and need to communicate with each other, but training data to build supporting MT systems is limited. The book discusses different characteristics of related languages with rich examples and draws connections between two problems: translation for related languages and transliteration. It shows how linguistic similarities can be utilized to learn MT systems for related languages with limited data. It comprehensively discusses the use of subword-level models and multilinguality to utilize these linguistic similarities. The second part of the book explores methods for machine transliteration involving related languages based on multilingual and unsupervised approaches. Through extensive experiments over a wide variety of languages, the efficacy of these methods is established. Features Novel methods for machine translation and transliteration between related languages, supported with experiments on a wide variety of languages. An overview of past literature on machine translation for related languages. A case study about machine translation for related languages between 10 major languages from India, which is one of the most linguistically diverse country in the world. The book presents important concepts and methods for machine translation involving related languages. In general, it serves as a good reference to NLP for related languages. It is intended for students, researchers and professionals interested in Machine Translation, Translation Studies, Multilingual Computing Machine and Natural Language Processing. It can be used as reference reading for courses in NLP and machine translation.Anoop Kunchukuttan is a Senior Applied Researcher at Microsoft India. His research spans various areas on multilingual and low-resource NLP. Pushpak Bhattacharyya is a Professor at the Department of Computer Science, IIT Bombay. His research areas are Natural Language Processing, Machine Learning and AI (NLP-ML-AI). Prof. Bhattacharyya has published more than 350 research papers in various areas of NLP.
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